Foreground Video Embedding via Depth-Based Segmentation
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Solution Overview
Problem
Conventional video processing techniques lack robust user control and interaction with backgrounds and virtual objects, limiting the user experience in embedding foreground videos into secondary backgrounds.
Innovation Solution
The method involves receiving depth and color images from a live video to identify and separate foreground and background, allowing user control inputs to embed the foreground video into a secondary background, enabling interaction with virtual objects within the background feed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional video processing techniques are used to embed foreground into background, then the basic embedding function is achieved, but user control and interaction with background and virtual objects is limited
Solution Approach 1:
The system implements feedback mechanisms where user control inputs (such as gestures or commands) are detected and processed to dynamically adjust the embedding parameters, positioning, and interaction with virtual objects in real-time, enabling active user control over the video composition
Solution Approach 2:
The system transitions from static background embedding to dynamic interaction by allowing real-time modification of foreground video placement, background selection, and virtual object behavior based on user inputs, making the system adaptable to different user actions and preferences
2Reliability
If conventional embedding techniques are used, then foreground video is inserted into background, but the video experience is not robust or immersive
Solution Approach 1:
The system segments the video processing into distinct modules: depth image processing for foreground extraction, color image processing for background identification, control input processing for user interaction, and rendering modules for composite video generation. This modular approach improves reliability while managing complexity through functional separation
Solution Approach 2:
The system introduces intermediary processing layers including depth image analysis as a mediator between the raw video feed and the final embedding operation, enabling more precise and reliable foreground-background separation while maintaining manageable processing complexity through intermediate representation
3Adaptability or versatility
If real-time embedding is implemented with user control, then interactivity is enhanced, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by pre-processing depth and color images to extract foreground and background information before the actual embedding operation, and by pre-loading virtual objects and background feeds into memory, enabling faster real-time rendering when user control inputs occur
Solution Approach 2:
The system employs periodic processing cycles where depth and color images are processed in alternating or synchronized frames, with control inputs triggering targeted processing only when needed, reducing overall computational load while maintaining real-time interactivity
Data Source
AI summary
A color image and a depth image of a live video are received. Each of the color image and the depth image are processed to identify the foreground and the background of the live video. The background of the live video is removed in order to create a foreground video that comprises the foreground of the live video. A control input may be received to control the embedding of the foreground video into a second background from a background feed. The background feed may also comprise virtual objects such that the foreground video may interact with the virtual objects.